1. Field of the Invention
This invention relates to object detection.
2. Description of the Prior Art
The following description relates to a problem present in the detection of various types of objects, but will be discussed with respect to face detection for clarity of the description.
Many human-face detection algorithms have been proposed in the literature, including the use of so-called eigenfaces, face template matching, deformable template matching or neural network classification. None of these is perfect, and each generally has associated advantages and disadvantages. None gives an absolutely reliable indication that an image contains a face; on the contrary, they are all based upon a probabilistic assessment, based on a mathematical analysis of the image, of whether the image has at least a certain likelihood of containing a face. Depending on their application, the algorithms generally have the threshold likelihood value set quite high, to try to avoid false detections of faces.
Object detection tends to be very processor-intensive. In situations where object detection has to be carried out in real time, it can be difficult to complete all of the object detection processing in the time allowed—e.g. one frame period of a video signal.